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DBMS > Google Cloud Spanner vs. MarkLogic vs. Sadas Engine vs. Teradata Aster

System Properties Comparison Google Cloud Spanner vs. MarkLogic vs. Sadas Engine vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonMarkLogic  Xexclude from comparisonSadas Engine  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Operational and transactional Enterprise NoSQL databaseSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.37
Rank#97  Overall
#50  Relational DBMS
Score7.08
Rank#56  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#5  Search engines
Score0.06
Rank#371  Overall
#155  Relational DBMS
Websitecloud.google.com/­spannerwww.marklogic.comwww.sadasengine.com
Technical documentationcloud.google.com/­spanner/­docsdocs.marklogic.comwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperGoogleMarkLogic Corp.SADAS s.r.l.Teradata
Initial release2017200120062005
Current release11.0, December 20228.0
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availablecommercial infofree trial version availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedLinux
OS X
Windows
AIX
Linux
Windows
Linux
Data schemeyesschema-free infoSchema can be enforcedyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyesnoyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011yes infoSQL92yesyes
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptnoR packages
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.yesnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationACID infocan act as a resource manager in an XA/JTA transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, with Range Indexesyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control at the document and subdocument levelsAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Google Cloud SpannerMarkLogicSadas EngineTeradata Aster
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